ELE528: INFORMATION THEORY
Spring 1995
Professor Sergio Verdú
1. SOURCE CODING
Noiseless source coding of memoryless sources - Asymptotic Equipartition Property - Divergence & Entropy - Variable Length Source - Coding Coding Theorem for Stationary Ergodic Sources - Lempel Ziv Algorithm and its optimality - Separate Encoding of Correlated Sources - Rate-Distortion Theory
2. CHANNEL CODING
Binary Hypothesis Testing: Bounds and Asymptotic Analysis - Properties of Divergence and Mutual Information - Codes and Bounds - Channels, Capacity, and Coding Theorem - Source Channel Separation
3. GAUSSIAN CHANNELS
Capacity of memoryless channels - Capacity of parallel channels - Colored noise channels
4. MULTIUSER INFORMATION THEORY
Multiaccess Channel - Coding theorem - Gaussian Multiple Access Channel